Financial Analysis

source("pgload.R")

tw2330 <- getSymbols("2330.tw",auto.assign = F,warnings = T,from="2000-01-01")

names(tw2330) <- c("Open","High","Low","Close","Volume","Adjust")

tw2330 %>% head

##               Open    High     Low   Close       Volume   Adjust
## 2000-01-04 69.6490 69.6490 68.4752 69.6490 200662321971 39.52547
## 2000-01-05 69.6490 71.2141 68.8663 71.2141 402466776297 40.41367
## 2000-01-06 70.8229 71.2141 69.6490 69.6490 197545701266 39.52547
## 2000-01-07 67.3013 68.4752 66.5186 67.6925 235270327441 38.41517
## 2000-01-10 69.6490 70.4314 68.4752 70.0402 276171665217 39.74748
## 2000-01-11 70.8229 71.6052 68.4752 68.8663 277769524211 39.08129

tw2330 %>%
  .$Close %>% 
  is.na() %>% 
  # which((.)==T)
  sum  -> NAvalue
tw2330 %>%
  .$Close %>% 
  length() -> AllValue

NAvalue/AllValue # 資料損失程度

## [1] 0.01854975

na.omit(tw2330) -> tw2330

tw2330 %>% 
  index(tw2330) -> Date 
  data.frame(Date,tw2330) %>% 
    as.tibble() -> tw2330_DF
rm(Date)

p <- tw2330_DF %>%
    # tail()
    filter(Date > ymd("20180101")) %>% 
    ggplot(aes(Date,Close)) + 
    geom_line() +
      labs(
        title ="Trade"
      )

ggplotly(p)

chart_Series(tw2330["2018"]) 

add_BBands()

add_MACD()

quantmod::add_EMA()

add_RSI()  -> x

x

裏面太多資訊 ， 想要做一個 策略判斷 logging >> 讀相關 判定